EDA for rowers examined at Irish rowing centre, Farran woods, Cork. 3/2/23

We use foodbook_daily_intakes which is the summarised version of the FB24 data. We further map the Meal into MealShort by factorising the meals in SNACK and MEAL.

koboData is the KoboToolbox survey data with the adjustment.

combinedProfiles is joining koboData and foodbook_daily_intakes

koboProfiles is subset of the koboData with the following column redefined

Number of subject at given icdas score 1
score countSubject
0 88
1 29
2 18
3 64
4 36
6 6
7 12
8 5
96 8
97 10
98 25
99 30

Fillings and dental caries summary for all athletes

Number of subject at given icdas score 2
score countSubject
0 88
1 6
2 76
3 74
4 45
5 23
6 4

Oral health by gender and sport (rowers v all others)

  • self reported oral health behaviours
  • combined ICDAS score 2 = count of all scores 3-6 (‘moderate and extensive decay’).

## mapping: x = ~last_dental_visit, colour = ~gender, fill = ~gender 
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack

## mapping: x = ~describe_health, colour = ~gender, fill = ~gender 
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack

## mapping: x = ~pain_12months, colour = ~gender, fill = ~gender 
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack

## mapping: x = ~teeth_affect_smiling, colour = ~gender, fill = ~gender 
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack

## mapping: x = ~frequency_sweets, colour = ~gender, fill = ~gender 
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack

## mapping: x = ~drinks_after_competitions, colour = ~gender, fill = ~gender 
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack

## # A tibble: 20 × 5
##    combined_icdas_score_2 sport_remap count total percentage
##                     <dbl> <chr>       <int> <int>      <dbl>
##  1                      0 Others          5    67     0.0746
##  2                      1 Others         12    67     0.179 
##  3                      2 Others         10    67     0.149 
##  4                      3 Others          5    67     0.0746
##  5                      4 Others          8    67     0.119 
##  6                      5 Others          5    67     0.0746
##  7                      6 Others          5    67     0.0746
##  8                      7 Others          6    67     0.0896
##  9                      8 Others          2    67     0.0299
## 10                      9 Others          7    67     0.104 
## 11                     13 Others          2    67     0.0299
## 12                      0 Rowing          4    21     0.190 
## 13                      1 Rowing          3    21     0.143 
## 14                      2 Rowing          1    21     0.0476
## 15                      3 Rowing          2    21     0.0952
## 16                      4 Rowing          1    21     0.0476
## 17                      5 Rowing          2    21     0.0952
## 18                      6 Rowing          3    21     0.143 
## 19                      7 Rowing          4    21     0.190 
## 20                      8 Rowing          1    21     0.0476

Nutrients

Mean intake= in a single meal or snack, mean of what was actually consumed (“average consumption”)

Mean daily intake= sum of total intake/no. of recalls when food actually consumed (if not consumed is not included in denominator)

dentalNutStats function: selected nutrients for dental impact “ENERGY (KCAL)”,“CHO”, “SUGARS”,“STARCH”- Uses Combined profile and fbSubjectIntakeLong: aggregated data by user so that we that we can calcluate mean intake by each participant to give:

total_consumptions=sum(consumption), max_daily_consumptions=max(consumption), mean_intake = mean(intake), max_intake = max(intake), sum_intake = sum(intake), recalls=n_distinct(Recall #)

mean_daily_intake = sum_intake / recalls

## Rows: 13 Columns: 1
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): GroupCodeShort
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Warning: Using an external vector in selections was deprecated in tidyselect 1.1.0.
## ℹ Please use `all_of()` or `any_of()` instead.
##   # Was:
##   data %>% select(dentalNutrients)
## 
##   # Now:
##   data %>% select(all_of(dentalNutrients))
## 
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

## Rows: 13 Columns: 1
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## chr (1): GroupCodeShort
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## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## Rows: 13 Columns: 1
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## Delimiter: ","
## chr (1): GroupCodeShort
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## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## Rows: 13 Columns: 1
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): GroupCodeShort
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.